HW-2 Yiğit Kutlu

Task a

Read the data and visualize one instance (all axes) from each class and try to relate the shape (time series) you see with the gestures shown in Figure 1

Comments on task a

It is not easy to compare 3D data to 2D data at the Table 1

But my guesses will be;

class 1 -> 4 class 2 -> 8 class 3 -> 7 class 4 -> 6 class 5 -> 5 class 6 -> 3 class 7 -> 2 class 8 -> 1

Task b

Comments on task b

We have performed PCA analysis on position data of 2 time series for each class. PCA component 1 gives best varience coverage with %54. So in order to reduce to 1 dimension component 1 is choosen. Comp.1 gives X value 0.209 Y value 0.723 and Z value 0.658. Mainly the weight of Y and Z components are much bigger than weight of X for component 1. So the X data have very little impact on component 1. As we observe from PCA results, component 2 is heavly depend on X.

We plotted 2 timeseries from each class. The classes 1 and 6 can be seperated with component 1, but I cannot observe any specific results for other classes excpet maybe class 5. The other classes are clustured together.

Since the effect of X is very low on component 1, I did not expected classes to be seperated entirely, and we also only covered the %54 of the varience.

It may also be wise to use acceleration data not the position data for PCA.

Task c

Comments on task c

The classes 5 and 6 gives similar but some opposite sign coefficients for X,Y and Z. When we look at the first component, the value of X is similar but values of Y and Z are opposite sign. Similar observations for comp2 and comp3. I would say these classes are similar but opposite directions like signs 3&4 or 5&6 from Figure1.

I would expect a better variance coverage from PCA when done in classes but that was not the case. Variance coverage of comp1 for all classes are near to result of overall PCA's first component.

Task d

Comments on task d

I did not observe any clusterings in classes execpt, class 4 which spans the left side of the graph and class 3 which spans the right side of the graph. Class 2 is observed to be centered on the graph but classes are overall mixed together. It is not a viable method to decide classes.